Dynamic quantum data output post-processing

ABSTRACT

Techniques for managing and compressing quantum output data (QOD) associated with quantum computing are presented. In response to receiving QOD from a quantum computer, a compressor component can compress QOD at first compression level to generate first compressed QOD, and can compress QOD at second compression level to generate second compressed QOD, the second compressed QOD can be less compressed than the first compressed QOD. Compressor management component (CMC) can determine whether first QOD includes sufficient data to enable it to be suitably processed by quantum logic. If so, CMC can allow first compressed QOD to continue to be sent to quantum logic and can discard second compressed QOD. If not sufficient, CMC can determine that second compressed QOD is to be processed by quantum logic. If CMC determines second compressed QOD does not include sufficient data, CMC can determine that the QOD is to be processed by quantum logic.

BACKGROUND

The subject disclosure relates to quantum computing using quantumcircuits. Quantum computing employs quantum physics to encode andprocess information rather than binary digital techniques based ontransistors. A quantum computing device can employ quantum bits (alsoreferred to as qubits) that operate according to the laws of quantumphysics and can exhibit phenomena such as superposition andentanglement. The superposition principle of quantum physics allowsqubits to be in a state that partially represent both a value of “1” anda value of “0” at the same time. The entanglement principle of quantumphysics allows qubits to be correlated with each other such that thecombined states of the qubits cannot be factored individual qubitstates. For instance, a state of a first qubit can depend on a state ofa second qubit. As such, a quantum circuit can employ qubits to encodeand process information in a manner that can be significantly differentfrom binary digital techniques based on transistors.

Quantum computing can be utilized to perform quantum programming.Quantum programming can involve the process of assembling sequences ofinstructions, which can be called quantum programs, that can be capableof running on a quantum computer. Each quantum program can be associatedwith a collection of quantum circuits. When a quantum program isexecuted, a result can be produced by the quantum computer. This dataresult often can comprise a relatively large amount of data that has togo through various post-processing, with the post-processing dataresults being provided to the user or service (e.g., user or servicerequesting the data results) and/or being stored in a data store. It cantake an undesirably long time to post-process the data results and themto the desired destination (e.g., user, service, or data store).

One approach for quantum computing and processing data involves aquantum processor unit that can be used to process a stream of inputdata. The quantum processor unit may operate as a quantum streamingkernel, which can preprocess data for a variety of classical or quantumdata processing applications. The quantum processor unit can process theinput data stream over time while producing an output data stream andmaintaining a coherent quantum state that depends on the history ofinput data. In some cases, the output from the quantum processor unitcan be combined with classical post-processing (e.g., a lineartransformation), and the measured output bits in each time step may thenbe used to predict features about the streaming input signal. However,while this traditional approach describes preprocessing data forclassical or quantum data processing applications, and combining theoutput from the quantum processor unit with classical post-processinge.g., a linear transformation) where measured output bits in each timestep may be used to predict features about the streaming input signal,this traditional approach does not address the issue of post-processingdata results, such as data results having a relatively large amount ofdata, produced as an output from a quantum computer to returnpost-processed data in a desirably fast manner to users or servicesdesiring such data results.

Another approach for quantum computing and processing data relates tousing a quantum autoencoder algorithm as a paradigm for compressingquantum data, that is, expressing a data set comprised of quantum statesusing a fewer number of qubits. However, this approach relates toimplementing a quantum encoder algorithm for generic quantum circuitsand does not address the issue of post-processing data results, such asdata results having a relatively large amount of data, produced as anoutput from a quantum computer to return post-processed data in adesirably fast manner to users or services desiring such data results.

These and other deficiencies of traditional approaches for processingdata associated with quantum computing can result in inefficient and/orineffective data processing associated with quantum computing.

SUMMARY

The following presents a summary to provide a basic understanding of oneor more embodiments of the disclosed subject matter. This summary is notintended to identify key or critical elements, or delineate any scope ofthe particular embodiments or any scope of the claims. Its sole purposeis to present concepts in a simplified form as a prelude to the moredetailed description that is presented later. In one or more embodimentsdescribed herein, systems, devices, structures, computer-implementedmethods, apparatuses, and/or computer program products that canfacilitate post-processing and compressing quantum output data areprovided.

According to an embodiment, a system comprising a memory that storescomputer-executable components; and a processor, operatively coupled tothe memory, that executes computer-executable components. Thecomputer-executable components can comprise a compressor component that,in response to receiving quantum output data, generates first compressedquantum output data based on compression of the quantum output data at afirst compression level, wherein the first compressed quantum outputdata is provided to quantum logic. The computer-executable componentsalso can include a compression management component that determineswhether the first compressed quantum output data includes sufficientdata to be processed by the quantum logic, based on a defined quantumlogic processing criterion, to determine whether the quantum logic is toprocess second compressed quantum output data that is a less compressedversion of the quantum output data than the first compressed quantumoutput data. Such embodiments of the system can provide a number ofadvantages, including that the system can more quickly and efficientlyprovide post-processing data results, which can be produced by thequantum logic from the quantum output data (as compressed ornon-compressed), to a desired intended recipient (e.g., user, a service,a data store) of such data results.

In some embodiments, in response to determining that the firstcompressed quantum output data does not include the sufficient data tobe processed by the quantum logic, the compression management componentcan determine that the second compressed quantum output data is to beprocessed by the quantum logic and can facilitate providing the secondcompressed quantum output data to the quantum logic for quantum logicprocessing. In certain embodiments, a machine learning component canadaptively determine or infer a second compression level and acompression algorithm to be used by a second compressor sub-componentbased on a result of performing a machine learning analysis on the firstcompressed quantum output data, previous data associated with previousquantum operations or a previous quantum program, or informationrelating to quantum circuits utilized by a quantum program to facilitategeneration of the quantum output data or utilized by the previousquantum program to facilitate generation of previous quantum outputdata. These embodiments of the system can provide a number ofadvantages, including that the system can have the advantage of quicklyand efficiently speeding up the post-processing of quantum output dataand providing post-processed data results to an intended recipient,and/or can have the advantage of reducing the amount of data (e.g.,amount of data of the data results) communicated to or stored by theintended recipient.

Another embodiment relates to a computer-implemented method thatcomprises, in response to receiving quantum output information,generating, by a system operatively coupled to a processor, firstcompressed quantum output information based on compressing the quantumoutput information at a first compression level, wherein the firstcompressed quantum output information is communicated to quantum logic.The computer-implemented method also comprises determining, by thesystem, whether the first compressed quantum output information hassufficient information to be processed by the quantum logic, inaccordance with a defined quantum logic processing criterion, todetermine whether the quantum logic is to process second compressedquantum output information that is a less compressed version of thequantum output information than the first compressed quantum outputinformation. Such embodiment of the method can provide a number ofadvantages, including that the method can more quickly and efficientlyprovide post-processing information results, which can be produced bythe quantum logic from the quantum output information (as compressed ornon-compressed), to a desired intended recipient (e.g., user, a service,a data store) of such information results.

In certain embodiments, the method can further comprise, in response todetermining that the first compressed quantum output information doesnot have the sufficient information to be processed by the quantumlogic, determining, by the system, that the second compressed quantumoutput information is to be processed by the quantum logic, andcommunicating, by the system, the second compressed quantum outputinformation to the quantum logic for quantum logic processing. Suchembodiments of the method can provide a number of advantages, includingthat the method can have the advantage of quickly and efficientlyspeeding up the post-processing of quantum output information andproviding post-processed information results to an intended recipient,and/or can have the advantage of reducing the amount of information(e.g., amount of information of the information results) provided to orstored by the intended recipient.

A further embodiment relates to a computer program product thatfacilitates compressing quantum output data generated by a quantumcomputing circuit, the computer program product comprising a computerreadable storage medium having program instructions embodied therewith.The program instructions are executable by a processor to cause theprocessor to, in response to receiving the quantum output data, generatefirst compressed quantum output data, based on compression of thequantum output data at a first compression level, wherein the firstcompressed quantum output data can be provided to quantum logic. Theprogram instructions also are executable by the processor to determinewhether the first compressed quantum output data includes an amount ofdata points, associated with the quantum output data, that is sufficientto be processed by the quantum logic, in accordance with a definedquantum logic processing criterion, to determine whether the quantumlogic is to process second compressed quantum output data, which can bea less compressed version of the quantum output data than the firstcompressed quantum output data.

In some embodiments, the program instructions also can be executable bythe processor to, in response to determining that the first compressedquantum output data does not include the amount of the data points thatis sufficient to be processed by the quantum logic, determine that thesecond compressed quantum output data is to be processed by the quantumlogic, wherein the second compressed quantum output data can have asecond data resolution that can be higher than a first data resolutionof the first compressed quantum output data, and can transmit the secondcompressed quantum output data to the quantum logic for quantum logicprocessing. These embodiments of the computer program product canprovide a number of advantages, including that the computer programproduct can have the advantage of quickly and efficiently increasing thespeed of the post-processing of quantum output data and providingpost-processed data results to an intended recipient, and/or can havethe advantage of reducing the amount of data (e.g., amount of data ofthe data results) communicated to or stored by the intended recipient.

These and other features will become apparent from the followingdetailed description of illustrative embodiments thereof, which is to beread in connection with the accompanying drawings.

DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a block diagram of an example, non-limiting systemthat can manage post-processing, including compression, of quantumoutput data that can be output as data results from a quantum computer,in accordance with various aspects and embodiments of the disclosedsubject matter.

FIG. 2 depicts a block diagram of another example, non-limiting systemthat can manage post-processing, including compression, of quantumoutput data that can be output as data results from a quantum computer,in accordance with various aspects and embodiments of the disclosedsubject matter.

FIG. 3 presents diagrams of example data resolutions associated withrespective data compression levels and a non-compressed level, inaccordance with various aspects and embodiments of the disclosed subjectmatter.

FIG. 4 illustrates a block diagram of an example, non-limiting systemthat can manage post-processing of quantum output data that can beoutput as data results from a quantum computer, and can employ machinelearning or artificial intelligence (AI) techniques and algorithms toadaptively determine a desirable compression level for use incompressing quantum output data, in accordance with various aspects andembodiments of the disclosed subject matter.

FIG. 5 depicts a block diagram of still another example, non-limitingsystem that can manage post-processing, including compression, ofquantum output data that can be output as data results from a quantumcomputer, in accordance with various aspects and embodiments of thedisclosed subject matter.

FIG. 6 illustrates a flow diagram of an example, non-limiting methodthat can control post-processing, including compression, of quantumoutput data that can be output as data results from a quantum computer,in accordance with various aspects and embodiments of the disclosedsubject matter.

FIG. 7 depicts a flow diagram of another example, non-limiting methodthat control post-processing, including compression, of quantum outputdata output as data results from a quantum computer, in accordance withvarious aspects and embodiments of the disclosed subject matter.

FIG. 8 illustrates a flow diagram of an example, non-limiting methodthat can adaptively determine a compression level and compressionalgorithm to use for compressing quantum output data, in accordance withvarious aspects and embodiments of the disclosed subject matter.

FIG. 9 illustrates a block diagram of an example, non-limiting operatingenvironment in which one or more embodiments described herein can befacilitated.

DETAILED DESCRIPTION

The following detailed description is merely illustrative and is notintended to limit embodiments and/or application or uses of embodiments.Furthermore, there is no intention to be bound by any expressed orimplied information presented in the preceding Background or Summarysections, or in the Detailed Description section.

One or more embodiments are now described with reference to thedrawings, wherein like referenced numerals are used to refer to likeelements throughout. In the following description, for purposes ofexplanation, numerous specific details are set forth in order to providea more thorough understanding of the one or more embodiments. It isevident, however, in various cases, that the one or more embodiments canbe practiced without these specific details.

Quantum programming can involve the process of assembling sequences ofinstructions, which can be called quantum programs, that can be capableof running on a quantum computer. Each quantum program can be associatedwith a collection of quantum circuits. When a quantum program isexecuted, a data result can be produced by the quantum computer. Thisdata result often can comprise a relatively large amount of data thathas to go through various post-processing, with the post-processing dataresults being provided to the user or service (e.g., user or servicerequesting the data results) and/or being stored in a data store. It cantake an undesirably long time to post-process the data results and themto the desired destination (e.g., user, service, or data store). It canbe desirable to manage such data results (e.g., quantum output data) ina desirable (e.g., proper, suitable, or optimal) way to post-process thedata results in a desirable (e.g., quick) manner and get thepost-processed data results to the requesting device (e.g., the devicethat submitted the job request to the quantum computer) or otherdestination, so that it can be utilized (e.g., consumed) by users orservices, and/or so that it can be stored in a data store.

One approach for quantum computing and processing data involves aquantum processor unit that can be used to process a stream of inputdata. The quantum processor unit may operate as a quantum streamingkernel, which can preprocess data for a variety of classical or quantumdata processing applications. The quantum processor unit can process theinput data stream over time while producing an output data stream andmaintaining a coherent quantum state that depends on the history ofinput data. In some cases, the output from the quantum processor unitcan be combined with classical post-processing (e.g., a lineartransformation), and the measured output bits in each time step may thenbe used to predict features about the streaming input signal. However,while this traditional approach describes preprocessing data forclassical or quantum data processing applications, and combining theoutput from the quantum processor unit with classical post-processinge.g., a linear transformation) where measured output bits in each timestep may be used to predict features about the streaming input signal,this traditional approach does not address the issue of post-processingdata results, such as data results having a relatively large amount ofdata, produced as an output from a quantum computer to returnpost-processed data in a desirably fast manner to users or servicesdesiring such data results.

Another approach for quantum computing and processing data relates tousing a quantum autoencoder algorithm as a paradigm for compressingquantum data, that is, expressing a data set comprised of quantum statesusing a fewer number of qubits. However, this approach relates toimplementing a quantum encoder algorithm for generic quantum circuitsand does not address the issue of post-processing data results, such asdata results having a relatively large amount of data, produced as anoutput from a quantum computer to return post-processed data in adesirably fast manner to users or services desiring such data results.

The disclosed subject matter can be implemented to produce a solution toall or at least some of these problems and/or other problems withtraditional quantum computing and post-processing techniques in the formof dynamic post-processing of quantum output data (QOD), includingdynamically determining a compressed stream of QOD, having a certaincompression level, that is suitable (e.g., contains sufficient data) tobe processed, and is to be processed, by a quantum logic component,and/or dynamically, automatically, and/or adaptively determining a levelof compression to apply to the stream of QOD to generate compressed QODthat is suitable to be processed by the quantum logic component.

To that end, the various aspects and embodiments herein relate totechniques for managing post-processing and compressing of QODassociated with quantum computing. The disclosed subject matter cancomprise a quantum computer component that can receive a job request andassociated input data. A quantum program can be associated with a set ofquantum circuits of the quantum computer component and can execute a setof instructions (e.g., a sequence of instructions) and use the set ofquantum circuits and a quantum algorithm to perform various quantumoperations and/or analysis on the input data and/or other relevant data.Based at least in part on the quantum operations and/or analysisperformed on the input data and/or other relevant data, and based atleast in part on the set of quantum circuits and quantum algorithm, thequantum computer component (e.g., the quantum program running on thequantum computer component) can produce QOD as a data result that can beoutput from the quantum computer component.

The disclosed subject matter also can comprise a compressor componentthat can receive the QOD from the quantum computer component. Inresponse to receiving the QOD from the quantum computer component, thecompressor component (e.g., employing a first compressor sub-component)can compress the QOD (e.g., as converted from analog to digital form) ata first compression level (e.g., a higher compression level) to generatefirst compressed QOD (e.g., a first compressed stream) having a firstdata resolution. The compressor component (e.g., employing a secondcompressor sub-component) also can compress the QOD at a secondcompression level (e.g., a relatively lower compression level) togenerate second compressed QOD (e.g., a second compressed stream) havinga second data resolution. The second compressed QOD can be a lesscompressed version of the QOD than the first compressed QOD, and thesecond data resolution can have a relatively higher data resolution thanthe first data resolution.

The disclosed subject matter can comprise a quantum logic component thatcan utilize quantum logic (e.g., quantum algorithm logic) to facilitatepost-processing the QOD (e.g., compressed or non-compressed QOD) toproduce useful data results that can be provided to a user or service,or can be stored in a data store. The first compressed QOD can beprovided to the quantum logic component for further processing, whereinthe first compressed QOD can be processed based at least in part on thequantum logic employed by the quantum logic component. While processingthe first compressed QOD, the quantum logic component can performvalidation checks on the results of processing the first compressed QODto determine whether the first compressed QOD includes sufficient data(e.g., sufficient data points) to enable the quantum logic component todesirably (e.g., suitably or acceptably) process the first compressedQOD using the quantum logic to produce a useful data result (e.g.,post-processed data result) as an output from the quantum logiccomponent.

In some embodiments, the compressor component also can communicate thesecond compressed QOD (e.g., second compressed stream) to the quantumlogic component at or near the same time the compressor component iscommunicating the first compressed QOD (e.g., first compressed stream)to the quantum logic component. In certain embodiments, while the secondcompressed stream can be communicated to the quantum logic component ator near the same time as the first compressed stream, the quantum logiccomponent typically will not process the second compressed stream if andwhile the quantum logic component is processing the first compressedstream. In such instances, if and while the quantum logic component isprocessing the first compressed stream, the second compressed stream canbe stored in a data store (e.g., buffer component or other data store)of or associated with the quantum logic component.

The disclosed subject matter further can comprise a compressormanagement component (CMC) that can be associated with the quantumcomputer, the compressor component, and the quantum logic component. TheCMC can manage the compression of the QOD, and also can manage theprovision of compressed data streams or the non-compressed QOD to thequantum logic component. In some embodiments, the CMC can determinewhether the first compressed QOD includes sufficient data to enable itto be desirably (e.g., suitably or acceptably) processed by the quantumlogic component, based at least in part on feedback information (e.g.,results of the validation checks) that can be received from the quantumlogic component, and in accordance with defined quantum logic criteria(e.g., a quantum logic criterion that can indicate whether a stream ofcompressed data includes sufficient data to enable it to be suitablyprocessed by the quantum logic component). If the CMC determines thatthe first compressed QOD includes sufficient data to enable it to bedesirably processed by the quantum logic component, the CMC can allowthe first compressed QOD to continue to be sent to and processed by thequantum logic component, and the CMC can discard or facilitatediscarding the second compressed QOD (and the non-compressed QOD). Ifthe CMC determines that the first compressed QOD does not includesufficient data to enable it to be desirably processed by the quantumlogic component, the CMC can determine that the second compressed QOD isto be processed by the quantum logic component.

In certain embodiments, the CMC can continue to monitor thepost-processing and can receive feedback information (e.g., results ofthe validation checks) regarding the second compressed QOD from thequantum logic component. Based at least in part on such feedbackinformation, the CMC can determine whether the second compressed QODincludes sufficient data to enable it to be desirably processed by thequantum logic component, in accordance with the defined quantum logiccriteria. If CMC determines the second compressed QOD does includesufficient data, the CMC can allow the second compressed QOD to continueto be sent to and processed by the quantum logic component, and the CMCcan discard or facilitate discarding the QOD (e.g., the non-compressedQOD stream). If CMC determines that the second compressed QOD does notinclude sufficient data, the CMC can determine that the QOD is to beprocessed by the quantum logic component.

In some embodiments, the CMC can employ a machine learning componentthat can utilize machine learning techniques and algorithms, orartificial intelligence (AI) techniques and algorithms, to perform ananalysis (e.g., machine learning analysis, AI analysis, or otheranalysis) on the first compressed QOD (or portion thereof), previousdata associated with quantum computing, quantum programs, or quantumcircuitry, and/or feedback information (e.g., results of validationchecks) relating to the first compressed QOD. Based at least in part onthe results of such analysis, the machine learning component candynamically, automatically, and/or adaptively determine, infer, or learna desirable (e.g., suitable or optimal) second compression algorithm andsecond compression level to use to compress the QOD to generate thesecond compressed QOD such that the second compressed QOD can contain,or at least can be predicted to contain, sufficient data to enable it tobe desirably processed by the quantum logic component, in accordancewith (e.g., to satisfy) the defined quantum logic criteria, as morefully described herein.

These and other aspects and embodiments of the disclosed subject matterwill now be described with respect to the drawings.

FIG. 1 illustrates a block diagram of an example, non-limiting system100 that can manage post-processing, including compression, of QOD thatcan be output as data results from a quantum computer, in accordancewith various aspects and embodiments of the disclosed subject matter.The system 100 can comprise a quantum computer component 102 that caninclude various quantum devices, quantum circuitry, and/or othercomponents (e.g., simulator components).

The system 100 also can comprise a quantum program 104 that can includea set of instructions (e.g., assembled sequence of instructions) thatcan be input to and run on the quantum computer component 102. Thequantum program 104 can be associated with a collection of quantumdevices, quantum circuitry, and/or other components of the quantumcomputer component 102, as indicated or determined by the instructionsof the quantum program 104. The quantum program 104 or quantum computercomponent 102 can receive input data upon which various operations(e.g., quantum operations) can be performed when the quantum program 104is executed, and data results, which also can be referred to as QOD, canbe produced as a result of the execution of the quantum program 104 andthe performance of operations on the input data and/or other data (e.g.,other relevant data). The QOD produced by a quantum program 104frequently can be a relatively large amount of data. It can be desirableto post-process such large amounts of QOD as quickly as possible, whilestill producing desirable (e.g., suitable, proper, and/or usable)post-process data results, so that such data results can be provided asquickly as is feasible to the user or service that is the intendedrecipient of such data results and/or to a data store for storage.

To facilitate desirably providing post-process data results in a quickand efficient manner, the system 100 can comprise a compressionmanagement component (CMC) 106 that can be associated with (e.g.,communicatively connected to) the quantum computer component 102. TheCMC 106 can desirably (e.g., efficiently, quickly, and optimally) managepost-processing, including compression, of QOD, which can be receivedfrom the quantum computer component 102, in accordance with definedcompression management criteria and defined quantum logic criteria.

The CMC 106 can comprise a compressor component 108 that can employ oneor more of various compression algorithms (e.g., lossless compressionalgorithms) to compress the QOD at various data resolution levels (e.g.,various levels of precision). Different compression algorithms cancompress the QOD at different speeds. For instance, a compressionalgorithm having a higher level of compression typically can compressthe QOD at a relatively fast speed, but typically can produce compresseddata that has a relatively lower data resolution level (e.g., relativelylower precision). Another compression algorithm having a relativelylower level of compression typically can compress the QOD at arelatively slower speed as compared to the higher compression level, buttypically can produce compressed data that has a relatively higher dataresolution level (e.g., relatively higher precision) than the compresseddata produced by the higher compression level.

The CMC 106, including the compressor component 108, can be associatedwith (e.g., communicatively connected to) a quantum logic component 110,and can desirably (e.g., quickly, efficiently, and suitably) provide(e.g., communicate or stream) compressed QOD to the quantum logiccomponent 110 for further post-processing. The quantum logic component110 can comprise quantum logic 112 (e.g., quantum algorithm logic) thatcan process the compressed QOD to produce data results (e.g.,post-processed data results) that can be provided to an intendedrecipient (e.g., user, service, or data store).

To facilitate desirable compression of the QOD, in accordance withvarious embodiments, the CMC 106 can dynamically determine (e.g.,dynamically or automatically) determine and facilitate generating acompressed stream of QOD, having a certain compression level, that canbe suitable (e.g., can contain sufficient data) to be desirably (e.g.,suitably or properly) processed, and is to be processed, by the quantumlogic component 110, in accordance with the defined quantum logiccriteria. The defined quantum logic criteria can comprise one or morecriterion that can indicate whether a stream of compressed data includessufficient data to enable it to be suitably processed by the quantumlogic component 110. In some embodiments, the CMC 106 can dynamically,automatically, and/or adaptively determine a level of compression toapply to the stream of QOD to generate compressed QOD that can besuitable to be processed by the quantum logic component 110, inaccordance with the defined quantum logic criteria.

In response to receiving the QOD from the quantum computer component102, the compressor component 108 can compress the QOD (e.g., asconverted from analog to digital form) at a first compression level(e.g., a relatively higher compression level), using a first compressionalgorithm, to generate first compressed QOD 114 (e.g., a first stream ofcompressed QOD) that can have a first data resolution level (e.g., arelatively lower data resolution). The compressor component 108 also cancompress the QOD at a second compression level (e.g., a relatively lowercompression level)), using a second compression algorithm, to generatesecond compressed QOD 116 (e.g., a second stream of compressed QOD) thatcan have a second data resolution level. The second compressed QOD 116can be a less compressed version of the QOD than the first compressedQOD 114, and the second data resolution level can have a relativelyhigher data resolution than the first data resolution level. In someembodiments, the compressor component 108 can begin compressing the QODat the second compression level at the same time, or substantially sametime (e.g., shortly after), the compressor component 108 beginscompressing the QOD at the first compression level, such that therespective streams are being compressed in parallel. In otherembodiments, the compressor component 108 can begin compressing the QODat the second compression level at a desired time after the compressorcomponent 108 begins compressing the QOD at the first compression level,such that at least portions of the respective streams are beingcompressed in parallel.

The CMC 106 can provide (e.g., can stream or communicate) the firstcompressed QOD 114 to the quantum logic component 110 for furtherprocessing. The quantum logic component 110 can process the firstcompressed QOD 114 using the quantum logic 112. While processing thefirst compressed QOD 114, the quantum logic component 110 can performvalidation checks on the results of processing the first compressed QOD114 to determine whether the first compressed QOD includes sufficientdata (e.g., sufficient data points) to enable the quantum logiccomponent 110 to desirably (e.g., suitably or acceptably) process thefirst compressed QOD 114 using the quantum logic 112 to produce a usefuldata result (e.g., post-processed data result) as an output from thequantum logic component 110, in accordance with the defined quantumlogic criteria.

In some embodiments, the CMC 106 (e.g., the compressor component 108 ofthe CMC 106) also can communicate (e.g., stream) the second compressedQOD 116 to the quantum logic component 110 at or near the same time theCMC 106 is communicating the first compressed QOD 114 to the quantumlogic component 110. In certain embodiments, while the second compressedQOD 116 can be communicated to the quantum logic component 110 at ornear the same time as the first compressed QOD 114, the quantum logiccomponent 110 typically will not process the second compressed QOD 116if and while the quantum logic component 110 is processing the firstcompressed QOD 114. In such instances, if and while the quantum logiccomponent 110 is processing the first compressed QOD 114, the secondcompressed QOD 116 can be stored in a data store (e.g., buffer componentor other data store) (not shown in FIG. 1) of or associated with thequantum logic component 110.

In still other embodiments, the CMC 106 also can communicate (e.g.,stream) the QOD 118 (non-compressed QOD) to the quantum logic component110 at or near the same time the CMC 106 is communicating the firstcompressed QOD 114 and/or the second compressed QOD 116 to the quantumlogic component 110. While the QOD 118 can be communicated to thequantum logic component 110 at or near the same time as the firstcompressed QOD 114 and/or the second compressed QOD 116, the quantumlogic component 110 typically will not process the QOD 118 if and whilethe quantum logic component 110 is processing the first compressed QOD114 or the second compressed QOD 116. In such instances, if and whilethe quantum logic component 110 is processing the first compressed QOD114 or the second compressed QOD 116, the QOD 118 can be stored in thedata store of or associated with the quantum logic component 110.

In some embodiments, the CMC 106 can receive feedback information 120from the quantum logic component 110, wherein the feedback information120 can comprise the validation check results relating to the processingof the first compressed QOD 114 by the quantum logic component 110. TheCMC 106 can determine whether the first compressed QOD 114 includessufficient data to enable it to be desirably (e.g., suitably oracceptably) processed by the quantum logic component 110, based at leastin part on the feedback information 120 (e.g., results of the validationchecks), and in accordance with (e.g., to satisfy) the defined quantumlogic criteria (e.g., a quantum logic criterion that can indicatewhether a stream of compressed data includes sufficient data to enableit to be suitably processed by the quantum logic component 110). Forexample, in determining whether the first compressed QOD 114 (or anydata stream under evaluation) includes sufficient data, the CMC 106 candetermine whether the first compressed QOD 114 includes an amount ofdata (e.g., a sufficient amount of data, or a sufficient amount of datapoints, in the portion of the data stream being evaluated) or has a dataresolution level that satisfies (e.g., meets or exceeds) a definedthreshold amount of data or a defined threshold data resolution level,respectively, in accordance with the defined compression managementcriteria and the defined quantum logic criteria, which, in part, cancorrespond to the defined compression management criteria with regard towhether there is sufficient data in the data stream to enable it to besuitably processed by the quantum logic component 110. The definedthreshold amount of data or the defined threshold data resolution leveleach can indicate whether the amount of data or the data resolutionlevel, respectively, is sufficient or suitable to enable such datastream to be desirably (e.g., suitably, properly, acceptably, oroptimally) processed by the quantum logic 112 of the quantum logiccomponent 110. If the defined threshold amount of data or definedthreshold data resolution level is satisfied, the data stream (e.g.,first compression QOD 114) can be desirably processed by the quantumlogic 112. If the defined threshold amount of data or defined thresholddata resolution level is not satisfied (e.g., is below the applicablethreshold), the data stream (e.g., first compression QOD 114) is notable to be desirably processed by the quantum logic 112. If the CMC 106determines that the first compressed QOD 114 includes sufficient data(e.g., satisfies the threshold data amount or data resolution level) toenable it to be desirably processed by the quantum logic component 110,the CMC 106 can allow the first compressed QOD 114 to continue to besent to (e.g., streamed to) and processed by the quantum logic component110, and the CMC 106 also can discard or facilitate discarding thesecond compressed QOD 116 (and the non-compressed QOD 118, except forany portion that remains to be compressed at the first compressionlevel).

If, instead, the CMC 106 determines that the first compressed QOD 114does not include sufficient data to enable it to be desirably processedby the quantum logic component 110, the CMC 106 can determine that thesecond compressed QOD 116 is to be processed by the quantum logiccomponent 110. In such instance, the CMC 106 can continue the streamingof the second compressed QOD 116 to the quantum logic component 110 forfurther post-processing, can discontinue the streaming of the firstcompressed QOD 114 (e.g., if any such data remains to be streamed) tothe quantum logic component 110, and can discard or facilitatediscarding the first compressed QOD 114 (e.g., if any such data remainsat the CMC 106).

In certain embodiments, the CMC 106 can continue to monitor thepost-processing and can receive further feedback information 120 (e.g.,results of the validation checks) regarding the second compressed QOD116 from the quantum logic component 110. Based at least in part on suchfeedback information 120, the CMC 106 can determine whether the secondcompressed QOD 116 includes sufficient data to enable it to be desirablyprocessed by the quantum logic component 110, in accordance with (e.g.,to satisfy) the defined quantum logic criteria. If the CMC 106determines that the second compressed QOD 116 does include sufficientdata, the CMC 106 can allow the second compressed QOD 116 to continue tobe sent to and processed by the quantum logic component 110, and the CMC106 can discard or facilitate discarding the QOD 118 (e.g., thenon-compressed QOD stream, except for any portion that remains to becompressed at the second compression level).

If, instead, based at least in part on the results of analyzing thefeedback information 120, the CMC 106 determines that the secondcompressed QOD 116 does not include sufficient data to enable it to bedesirably processed by the quantum logic component 110, the CMC 106 candetermine that the QOD 118 is to be processed by the quantum logiccomponent 110. In such instance, the CMC 106 can continue the streamingof the QOD 118 to the quantum logic component 110 for furtherpost-processing, can discontinue the streaming of the second compressedQOD 116 (e.g., if any such data remains to be streamed) to the quantumlogic component 110, and can discard or facilitate discarding the secondcompressed QOD 116 (e.g., if any such data remains at the CMC 106).

The disclosed subject matter, by respectively compressing the QOD 118 atrespective compression levels, in parallel, and employing the CMC 106 todesirably (e.g., suitably, efficiently, and/or optimally) manage therespective compression of the QOD 118 and determine which compressed QODstream is to be processed by the quantum logic component 110 at a giventime, can have the advantage of quickly and efficiently speeding up thepost-processing of data results (e.g., QOD) and providing thepost-processed data results to an intended recipient (e.g., user, aservice, a data store), and/or the advantage of reducing the amount ofdata (e.g., amount of data of the data results) communicated to orstored by the intended recipient, as compared to traditional techniquesfor handling quantum data results produced by a quantum computer.

Referring to FIG. 2, FIG. 2 depicts a block diagram of another example,non-limiting system 200 that can manage post-processing, includingcompression, of QOD that can be output as data results from a quantumcomputer, in accordance with various aspects and embodiments of thedisclosed subject matter. Repetitive description of like elementsemployed in other embodiments described herein is or may be omitted forsake of brevity.

The system 200 can comprise a quantum computer component 202, a quantumprogram 204, a CMC 206, a compressor component 208, and a quantum logiccomponent 210, which can include quantum logic 212 (e.g., quantumalgorithm logic). The CMC 206 can comprise (as depicted in FIG. 2) or beassociated with an analog-to-digital component (ADC) 214 that canreceive the QOD, in analog form (e.g., as an analog streaming signal),from the quantum computer component 202 and can convert the analog QODto digital QOD 216.

The compressor component 208 can receive the digital QOD 216 from theADC 214. In some embodiments, the compressor component 208 can comprisea first compressor sub-component (1^(st) COMP SUB-C) 218 (e.g., firstcompressor unit) and a second compressor sub-component (2^(nd) COMPSUB-C) 220 (e.g., second compressor unit) that can receive the QOD 216(e.g., digital QOD). In response to receiving the QOD 216, the firstcompressor sub-component 218 can compress the QOD 216 at a firstcompression level (e.g., a relatively higher compression level), basedat least in part on a first compression algorithm, to generate firstcompressed QOD 222 (e.g., a first compressed stream) having a first dataresolution level (1^(st) RES LEVEL) 224. The CMC 206, employing thefirst compressor sub-component 218, can provide, via a communicationchannel (COMM CHANNEL) 226, the first compressed QOD 222 to the quantumlogic component 210 for further processing. The quantum logic component210 can process (e.g., further post-process), or at least begin toprocess, the first compressed QOD 222 based at least in part on thequantum logic 212 employed by the quantum logic component 210.

The second compressor sub-component 220 can compress the QOD at a secondcompression level (e.g., a relatively lower compression level than thefirst compression level), based at least in part on a second compressionalgorithm, to generate second compressed QOD 228 that can have a seconddata resolution level (2^(nd) RES LEVEL) 230. The second compressed QOD228 can be a less compressed version of the QOD 216 than the firstcompressed QOD 222, and the second data resolution level 230 can have arelatively higher data resolution than the first data resolution level224.

In some embodiments, to facilitate determining the second compressionlevel and/or second compression algorithm to be used by the secondcompressor sub-component 220, the CMC 206 can employ machine learningtechniques and algorithms, or AI techniques and algorithms, to performan analysis (e.g., machine learning analysis, AI analysis, or otheranalysis) on the first compressed QOD 222 (or portion thereof), previousdata associated with the previous quantum computing, previous quantumprograms, or quantum circuitry, and/or feedback information (e.g.,results of validation checks) relating to the first compressed QOD 222.Based at least in part on the results of such analysis, the CMC 206 candynamically, automatically, and/or adaptively determine, infer, or learna desirable (e.g., suitable or optimal) second compression algorithm andthe second compression level to use to compress the QOD 216 to generatethe second compressed QOD 228 such that the second compressed QOD 228can contain, or at least can be predicted to contain, sufficient data toenable it to be desirably processed by the quantum logic component 210,in accordance with (e.g., to satisfy) the defined quantum logiccriteria, as more fully described herein.

Referring briefly to FIG. 3 (along with FIG. 2), FIG. 3 presentsdiagrams of example data resolutions 300 associated with respective datacompression levels and a non-compressed level, in accordance withvarious aspects and embodiments of the disclosed subject matter. As canbe observed in the example data resolutions 300, the first dataresolution level 224 can comprise a first set (e.g., number) of datapoints 302, the second data resolution level 230 can comprise a secondset of data points 304, and a third data resolution level (3^(rd) RESLEVEL) 232 can comprise a third set of data points 306, wherein thethird data resolution level 232, and associated third set of data points306, can be associated with the QOD 216. As also can be observed fromthe example data resolutions 300, the second data resolution level 230can be higher than the first data resolution level 224, and accordingly,the second set of data points 304 associated with the second dataresolution level 230 can have more data points than the first set ofdata points 302 associated with the first data resolution level 224.Further, as can be observed from the example data resolutions 300, thethird data resolution level 232 can be higher than the second dataresolution level 230 as well as the first data resolution level 224, andaccordingly, the third set of data points 306 associated with the thirddata resolution level 232 can have more data points than the second setof data points 304 associated with the second data resolution level 230as well as the first set of data points 302 associated with the firstdata resolution level 224.

In some embodiments, the second compressor sub-component 220 cancommunicate the second compressed QOD 228 to the quantum logic component210 at or near the same time the first compressor sub-component 218 iscommunicating the first compressed QOD 222 to the quantum logiccomponent 210. In certain embodiments, while the second compressorsub-component 220 is communicating (e.g., streaming) the secondcompressed QOD 228 to the quantum logic component 210 at or near thesame time as the first compressor sub-component 218 is communicating thefirst compressed QOD 222 to the quantum logic component 210, the quantumlogic component 210 typically will not process the second compressed QOD228 if and while the quantum logic component 210 is processing the firstcompressed QOD 222. In such instances, if and while the quantum logiccomponent 210 is processing the first compressed QOD 222, the secondcompressed QOD 228 can be stored in a data store of or associated withthe quantum logic component 210.

While processing the first compressed QOD 222, the quantum logiccomponent 210 can perform validation checks on the results (e.g.,post-processing data results) of processing the first compressed QOD 222to determine whether the first compressed QOD 222 includes sufficientdata to enable the quantum logic component 210 to desirably (e.g.,suitably or acceptably) process the first compressed QOD 222 using thequantum logic 212 in order to produce a desirable (e.g., suitable,acceptable, or useful) data result (e.g., post-processed data result) asan output from the quantum logic component 210.

In some embodiments, the CMC 206 can determine whether the firstcompressed QOD 222 includes sufficient data to enable it to be desirably(e.g., suitably or acceptably) processed by the quantum logic component210, based at least in part on feedback information 234 (e.g., resultsof the validation checks) that can be received from the quantum logiccomponent 210, and in accordance with the defined quantum logiccriteria. If the CMC 206 determines that the first compressed QOD 222includes sufficient data to enable it to be desirably processed by thequantum logic component 210, the CMC 206 can allow the first compressorsub-component 218 to continue to send the first compressed QOD 222 tothe quantum logic component 210 for processing by the quantum logiccomponent 210, and the CMC 206 can discard or facilitate discarding thesecond compressed QOD 228 (and the non-compressed QOD 216, except forany portion of such QOD 216 that remains to be compressed by the firstcompressor sub-component 218).

If, instead, based at least in part on the results of analyzing thefeedback information 234, the CMC 206 determines that the firstcompressed QOD 222 does not include sufficient data to enable it to bedesirably processed by the quantum logic component 210, the CMC 206 candetermine that the second compressed QOD 228 is to be processed by thequantum logic component 210, in accordance with the defined compressionmanagement criteria and the defined quantum logic criteria. In suchinstance, the CMC 206 can control the second compressor sub-component220 to have the second compressor sub-component 220 continue to compressthe QOD 216 at the second compression level to generate the secondcompressed QOD 228 and stream the second compressed QOD 228 to thequantum logic component 210 for further post-processing. The CMC 206also can control the first compressor sub-component 218 to discontinuethe compressing of the QOD 216 at the first compression level anddiscontinue the streaming of the first compressed QOD 222 (e.g., if anysuch data remains to be streamed) to the quantum logic component 210.The CMC 206 also can discard or facilitate discarding the firstcompressed QOD 222 (e.g., if any such data remains at the CMC 206).

The quantum logic component 210 can proceed to process the secondcompressed QOD 228, using the quantum logic 212. The quantum logiccomponent 210 also can perform validation checks on the results (e.g.,post-processing data results) of processing the second compressed QOD228 to determine whether the second compressed QOD 228 includessufficient data to enable the quantum logic component 210 to desirablyprocess the second compressed QOD 228 using the quantum logic 212 inorder to produce a desirable data result as an output from the quantumlogic component 210, in accordance with the defined quantum logiccriteria.

The CMC 206 can continue to monitor the post-processing and can receivefurther feedback information 234 (e.g., results of the validationchecks) regarding the second compressed QOD 228 from the quantum logiccomponent 210. Based at least in part on such feedback information 234,the CMC 206 can determine whether the second compressed QOD 228 containssufficient data to enable it to be desirably processed by the quantumlogic component 210, in accordance with (e.g., to satisfy) the definedquantum logic criteria. If the CMC 206 determines that the secondcompressed QOD 228 does contain sufficient data, the CMC 206 can controlthe second compressor sub-component 220 to have the second compressorsub-component continue to generate the second compressed QOD 228 andsend it to the quantum logic component 210 for further processing, andthe quantum logic component 210 can continue to process the secondcompressed QOD 228 using the quantum logic 212. The CMC 206 also candiscard or facilitate discarding the QOD 216 (e.g., the non-compressedQOD stream, except for any portion of the QOD 216 that remains to becompressed at the second compression level).

If, instead, based at least in part on the results of analyzing thefeedback information 234, the CMC 206 determines that the secondcompressed QOD 228 does not contain sufficient data to enable it to bedesirably processed by the quantum logic component 210, the CMC 206 candetermine that the QOD 216 is to be processed by the quantum logiccomponent 210. In such instance, the CMC 206 can continue the streamingof the QOD 216 to the quantum logic component 210 for furtherpost-processing by the quantum logic component 210. The CMC 206 also cancontrol the second compressor sub-component 220 to discontinue thestreaming of the second compressed QOD 228 (e.g., if any such dataremains to be streamed) to the quantum logic component 210. The CMC 206also can discard or facilitate discarding the second compressed QOD 228(e.g., if any such data remains at the CMC 206).

The disclosed subject matter, by employing multiple compressorsub-components (e.g., 218 and 220) to respective compress the QOD 216 atrespective compression levels and employing the CMC 206 to desirably(e.g., suitably, efficiently, and/or optimally) manage the respectivecompression of the QOD 216 and determine which compressed QOD stream isto be processed by the quantum logic component 210 at a given time, canhave the advantage of quickly and efficiently speeding up thepost-processing of data results (e.g., QOD) and providing thepost-processed data results to an intended recipient (e.g., user, aservice, a data store), and/or can have the advantage of reducing theamount of data (e.g., amount of data of the data results) communicatedto or stored by the intended recipient, as compared to traditionaltechniques for handling quantum data results produced by a quantumcomputer. The disclosed subject matter, by employing machine learningtechniques and algorithms, or AI techniques and algorithms, todynamically, automatically, and/or adaptively determine, infer, or learna desirable (e.g., suitable or optimal) compression algorithm (e.g., thesecond compression algorithm) and compression level (e.g., the secondcompression level) to use to compress QOD to generate compressed QODsuch that the compressed QOD can include, or at least can be predictedto include, sufficient data to enable it to be desirably processed bythe quantum logic, also can have the advantage of quickly andefficiently speeding up the post-processing of data results andproviding the post-processed data results to an intended recipient, ascompared to traditional techniques for handling quantum data resultsproduced by a quantum computer.

Turning to FIG. 4, FIG. 4 illustrates a block diagram of an example,non-limiting system 400 that can manage post-processing of QOD that canbe output as data results from a quantum computer, and can employmachine learning or AI techniques and algorithms to adaptively determinea desirable compression level for use in compressing QOD, in accordancewith various aspects and embodiments of the disclosed subject matter.Repetitive description of like elements employed in other embodimentsdescribed herein is or may be omitted for sake of brevity.

The system 400 can comprise a quantum computer component 402, a quantumprogram 404, a CMC 406, a compressor component 408, and a quantum logiccomponent 410, which can include quantum logic 412 (e.g., quantumalgorithm logic). The CMC 406 can comprise (as depicted in FIG. 4) or beassociated with an ADC 414 that can receive the QOD, in analog form(e.g., as an analog streaming signal), from the quantum computercomponent 402 and can convert the analog QOD to digital QOD 416.

The compressor component 408 can receive the digital QOD 416 from theADC 414. In some embodiments, the compressor component 408 can comprisea first compressor sub-component 418 (e.g., first compressor unit) and asecond compressor sub-component 420 (e.g., second compressor unit) thatcan receive the QOD 416. The first compressor sub-component 418 cancompress the QOD 416 at a first compression level (e.g., a relativelyhigher compression level), based at least in part on a first compressionalgorithm, to generate first compressed QOD 422 (e.g., a firstcompressed stream) having a first data resolution level, as more fullydescribed herein. The CMC 406, employing the first compressorsub-component 418, can provide the first compressed QOD 422 to thequantum logic component 410 for further processing. The quantum logiccomponent 410 can process (e.g., further post-process), or at leastbegin to process, the first compressed QOD 422 based at least in part onthe quantum logic 412 employed by the quantum logic component 410.

The quantum logic component 410 also can perform validation checks onthe data results produced by the quantum logic component 410 tofacilitate determining whether the first compressed QOD 422 is providingsufficient data to the quantum logic 412 to enable the quantum logic 412to desirably (e.g., suitably, properly, or optimally) process the firstcompressed QOD 422 to produce desirable (e.g., suitable, proper, orusable) data results, in accordance with the defined quantum logiccriteria. The CMC 406 can receive feedback information 424 from thequantum logic component 410, wherein the feedback information 424 cancomprise the validation check results relating to the processing of thefirst compressed QOD 422 by the quantum logic component 410.

Based at least in part on the results of analyzing the feedbackinformation 424, the CMC 406 can determine whether the first compressedQOD 422 includes sufficient data to enable the quantum logic 412 todesirably process the first compressed QOD 422, in accordance with thedefined quantum logic criteria. Based at least in part on the results ofsuch determination regarding the whether the first compressed QOD 422includes sufficient data, the CMC 406 can determine whether the firstcompressed QOD 422 is to continue to be provided to and processed by thequantum logic component 410 or whether the quantum logic component 410is to instead process second compressed QOD 426, having a second dataresolution level (e.g., a higher data resolution level than the firstdata resolution level), that can be generated by the second compressorsub-component 420 compressing the QOD 416 at a second compression level(e.g., a relatively lower compression level than the first compressionlevel).

In accordance with various embodiments, to facilitate determining adesirable second compression level and second compression algorithm, theCMC 406 can comprise a machine learning component (MLC) 428 that canemploy machine learning techniques and algorithms, and/or AI techniquesand algorithms, to dynamically, automatically, or adaptively determine,infer, or learn a desirable second compression level and secondcompression algorithm for desirably compressing the QOD 416 to producesecond compressed QOD 426 that can be desirably processed, or at leastcan be predicted to be suitable to be desirably processed, by thequantum logic component 410 to enable the quantum logic component 410 toproduce desirable (e.g., suitable, proper, or usable) data results. Themachine learning component 428 can receive the first compressed QOD 422,or a portion of that first compressed data stream, from the firstcompressor sub-component 418. The machine learning component 428 alsocan receive previous data 430 relating to the previous quantumoperations performed by the quantum computer component 402 and/orprevious quantum programs from a data store (e.g., a data store of theCMC 406, the quantum computer component 402, or another component of thesystem 400). The previous data 430 can include, for example, previousQOD associated with previous quantum programs that have been executed bythe quantum computer component 402, information regarding previousgroups of quantum circuits and quantum devices of the quantum computercomponent 402 that were used with the previous quantum programs, and/orprevious input data processed by the previous quantum programs. Theprevious data 430 also can include information relating to compressionlevels and compression algorithms that have previously been used, suchas, for example, previous compression levels and compression algorithmsthat have produced desirable compressed QOD that includes sufficientdata to satisfy the defined quantum logic criteria. In certainembodiments, the machine learning component 428 also can receive thefeedback information 424 relating to the first compressed QOD 422 fromthe quantum logic component 410.

The machine learning component 428 can analyze (e.g., can perform amachine learning, AI analysis, or other analysis on) the firstcompressed QOD 422, the previous data 430 relating to the previousquantum operations, and/or the feedback information 424. As an examplepart of such analysis, the machine learning component 428 can look forpatterns in the QOD 416 that are similar to patterns of previous QODand/or other similarities between the QOD 416 and the previous QOD inrelation to a compression level(s) and compression algorithm(s) thatproduced desirable compressed QOD (e.g., that satisfied the definedquantum logic criteria), can look for patterns in the first compressedQOD 422 that are similar to patterns of previous first compressed QODand/or other similarities between the first compressed QOD 422 and theprevious first compressed QOD in relation to a compression level(s) andcompression algorithm(s) that produced desirable compressed QOD, and/orcan look for patterns with regard to the quantum program 404 andassociated quantum circuitry that are similar to patterns of previousquantum programs and associated quantum circuitry and/or othersimilarities between the quantum program 404 and associated quantumcircuitry and the previous quantum programs and associated quantumcircuitry in relation to a compression level(s) and compressionalgorithm(s) that produced desirable compressed QOD, etc.

Based at least in part on the results of the analysis (e.g., machinelearning analysis, AI analysis, or other analysis), the machine learningcomponent 428 can dynamically, automatically, or adaptively determine,infer, or learn a second compression level and second compressionalgorithm where compression of the QOD 416 at the second compressionlevel, using the second compression algorithm, can produce secondcompressed QOD 426 that can include, or can be predicted to contain,sufficient data such that the second compressed QOD 426 can be desirably(e.g., suitably or properly) processed by the quantum logic component410, in accordance with (e.g., to satisfy) the defined quantum logicprocessing criteria.

In some embodiments, the CMC 406 can control operation of the secondcompressor sub-component 420 and selection of the second compressionlevel and second compression algorithm until the machine learningcomponent 428 is able to perform the analysis on the first compressedQOD 422, the previous data 430 relating to the previous quantumoperations, and/or the feedback information 424, and determine thesecond compression level and second compression algorithm to be used bythe second compressor sub-component 420, in accordance with applicablecompression management criteria. In such instances, the CMC 406 can havethe second compressor sub-component 420 begin compressing the QOD 416 atthe second compression level, based at least in part on the secondcompression algorithm, a relatively short time after the firstcompressor sub-component 418 starts compressing the QOD 416, forexample, once the machine learning component 428 has determined thesecond compression level and second compression algorithm.

In other embodiments, the CMC 406 can select an initial secondcompression level and initial second compression algorithm to be used bythe second compressor sub-component 420, and can control operation ofthe second compressor sub-component 420 to have the second compressorsub-component 420 begin compressing the QOD 416 at the initial secondcompression level, based at least in part on the initial secondcompression algorithm, at the same time or substantially the same timeas the first compressor sub-component 418 begins compressing the QOD 416at the first compression level, in accordance with applicablecompression management criteria. The second compressor sub-component 420can send the initial second compressed QOD to the quantum logiccomponent 410 for storage (e.g., temporary storage or buffering) untilthe CMC 406 determines whether the initial second compressed QOD is tobe processed by the quantum logic component 410, or whether the firstcompressed QOD 422 is to continue to be processed by the quantum logiccomponent 410, or whether there is an adapted second compression leveland adapted second compression algorithm, as determined by the machinelearning component 428, that are to be used by the second compressorsub-component 420 instead of the initial second compression level andinitial second compression algorithm.

If the CMC 406 determines that the adapted second compression level andadapted second compression algorithm are to be used by the secondcompressor sub-component 420, the CMC 406 can control the secondcompressor sub-component 420 to have it discontinue using the initialsecond compression level and initial second compression algorithm andbegin using the adapted second compression level and adapted secondcompression algorithm, in accordance with the defined compressionmanagement criteria and the defined quantum logic criteria. In suchcase, the second compressor sub-component 420 can generate secondcompressed QOD (e.g., 426) at the adapted second compression level,based at least in part on the adapted second compression algorithm, andcan send the second compressed QOD to the quantum logic component 410for temporary storage until processed or discarded, or for processing bythe quantum logic component 410 if the CMC 406 determines that the firstcompressed QOD 422 does not include sufficient data to be desirablyprocessed by the quantum logic component 410 to satisfy the definedquantum logic criteria.

While the first compressed QOD 422 is being processed by the quantumlogic component 410, the CMC 406 can determine whether the firstcompressed QOD 422 contains sufficient data to enable it to be desirablyprocessed by the quantum logic component 410, based at least in part onthe feedback information 424, and in accordance with the defined quantumlogic criteria. If the CMC 406 determines that the first compressed QOD422 includes sufficient data to enable it to be desirably processed bythe quantum logic component 410, the CMC 406 can allow the firstcompressed QOD 422 to continue to be sent to (e.g., streamed to) andprocessed by the quantum logic component 410, and the CMC 406 also candiscard or facilitate discarding the (initial or adapted) secondcompressed QOD 426 (and the non-compressed QOD 416, except for anyportion that remains to be compressed at the first compression level).

If, instead, based at least in part on the results of analyzing thefeedback information 424, the CMC 406 determines that the firstcompressed QOD 422 does not contain sufficient data to enable it to bedesirably processed by the quantum logic component 410, the CMC 406 candetermine that the (initial or adapted) second compressed QOD 426 is tobe processed by the quantum logic component 410. In such instance, theCMC 406 can control the second compressor sub-component 420 to have thesecond compressor sub-component 420 continue to compress the QOD 416 atthe (initial or adapted) second compression level to generate the(initial or adapted) second compressed QOD 426 and stream the secondcompressed QOD 426 to the quantum logic component 410 for furtherpost-processing. The CMC 406 also can control the first compressorsub-component 418 to discontinue the compressing of the QOD 416 anddiscontinue the streaming of the first compressed QOD 422 (e.g., if anysuch data remains to be streamed) to the quantum logic component 410.The CMC 406 also can discard or facilitate discarding the firstcompressed QOD 422 (e.g., if any such data remains at the CMC 406).

The quantum logic component 210 can proceed to process the secondcompressed QOD 426, using the quantum logic 412. The quantum logiccomponent 410 also can perform validation checks on the results (e.g.,post-processing data results) of processing the second compressed QOD426 to determine whether the second compressed QOD 426 includessufficient data to enable the quantum logic component 410 to desirablyprocess the second compressed QOD 426 using the quantum logic 412 inorder to produce a desirable data result as an output from the quantumlogic component 410, in accordance with the defined quantum logiccriteria.

The CMC 406 can continue to monitor the post-processing and can receivefurther feedback information 424 (e.g., results of the validationchecks) regarding the (initial or adapted) second compressed QOD 426from the quantum logic component 410. Based at least in part on suchfeedback information 424, the CMC 406 can determine whether the secondcompressed QOD 426 contains sufficient data to enable it to be desirablyprocessed by the quantum logic component 410, in accordance with (e.g.,to satisfy) the defined quantum logic criteria. If the CMC 406determines that the second compressed QOD 426 does contain sufficientdata, the CMC 406 can control the second compressor sub-component 420 tohave the second compressor sub-component 420 continue to generate thesecond compressed QOD 426 and send it to the quantum logic component 410for further processing, and the quantum logic component 410 can continueto process the second compressed QOD 426 using the quantum logic 412.The CMC 406 also can discard or facilitate discarding the QOD 416 (e.g.,the non-compressed QOD stream, except for any portion of the QOD 416that remains to be compressed at the second compression level).

If, instead, based at least in part on the results of analyzing thefeedback information 424, the CMC 406 determines that the secondcompressed QOD 426 does not contain sufficient data to enable it to bedesirably processed by the quantum logic component 410, the CMC 406 candetermine that the QOD 416 is to be processed by the quantum logiccomponent 410. In such instance, the CMC 406 can continue the streamingof the QOD 416 to the quantum logic component 410 for furtherpost-processing by the quantum logic component 410. The CMC 406 also cancontrol the second compressor sub-component 420 to discontinue thestreaming of the second compressed QOD 426 (e.g., if any such dataremains to be streamed) to the quantum logic component 410. The CMC 406also can discard or facilitate discarding the second compressed QOD 426(e.g., if any such data remains at the CMC 406).

In certain embodiments, the compressor component 408 can comprise (e.g.,optionally can comprise) another compressor sub-component(s) (OTHER COMPSUB-C) 432 (e.g., a third compressor sub-component) that can compressthe QOD 416 at another (e.g., third) compression level using another(e.g., third) compression algorithm. In such embodiments, if the secondcompressed QOD 426 is determined to not contain sufficient data fordesirable processing by the quantum logic component 410, the CMC 406 canswitch to the other compressor sub-component 432 (instead of switchingto the non-compressed QOD 416) to have the other compressorsub-component 432 compress the QOD 416 at the other compression level(e.g., a lower compression level than the second compression level),based at least in part on the other compression algorithm, to generateanother (e.g., third) compressed QOD 434 that can be sent to the quantumlogic component 410 for processing. If, after further monitoring andanalysis, the CMC 406 determines that none of the compressed QOD streamsare suitable for processing by the quantum logic component 410, the CMC406 can determine that the non-compressed QOD 416 is to be processed bythe quantum logic component 410.

The system 400 also can comprise a processor component (PROC COMP) 436that can work in conjunction with the other components (e.g., the CMC406, quantum logic component 410, and/or data store 438, . . . ) tofacilitate performing the various functions of the system 400. Theprocessor component 436 can employ one or more processors,microprocessors, or controllers that can process data, such asinformation relating to QOD, compressed QOD, quantum programs, quantumcircuitry, quantum devices, quantum algorithm logic, feedbackinformation, defined compression management criteria, defined quantumlogic criteria, data compression algorithms, machine learningalgorithms, AI algorithms, ADC algorithms, traffic flows, policies,protocols, interfaces, tools, and/or other information, to facilitateoperation of the system 400, as more fully disclosed herein, and controldata flow between the system 400 and other components (e.g., quantumcomputer component 402, quantum programs, data storage devices, userdevices or end-point devices, or other computing or communicationdevices) associated with (e.g., connected to) the system 400.

The data store 438 can store data structures (e.g., user data,metadata), code structure(s) (e.g., modules, objects, hashes, classes,procedures) or instructions, information relating to QOD, compressedQOD, quantum programs, quantum circuitry, quantum devices, quantumalgorithm logic, feedback information, defined compression managementcriteria, defined quantum logic criteria, data compression algorithms,machine learning algorithms, AI algorithms, ADC algorithms, trafficflows, policies, protocols, interfaces, tools, and/or other information,to facilitate controlling operations associated with the system 400. Inan aspect, the processor component 436 can be functionally coupled(e.g., through a memory bus) to the data store 438 in order to store andretrieve information desired to operate and/or confer functionality, atleast in part, to the CMC 406, quantum logic component 410, and/or datastore 438, etc., and/or substantially any other operational aspects ofthe system 400.

Referring to FIG. 5, FIG. 5 depicts a block diagram of still anotherexample, non-limiting system 500 that can manage post-processing,including compression, of QOD that can be output as data results from aquantum computer, in accordance with various aspects and embodiments ofthe disclosed subject matter. The system 500 can comprise a quantumcomputer component 502, which can comprise various quantum units thatcan be utilized to perform quantum operations on data to produce QOD(e.g., quantum data results). The system 500 also can include a jobsystem 504 that can generate job requests and send the job requests forprocessing by the quantum computer component 502. In connection withsending a job request to the quantum computer component 502, adaptivecompilation 506 can be performed to facilitate putting information andinstructions relating to the job requests in a desirable format for thequantum computer component 502 so that the quantum computer component502 can be able to process the job request. The adaptive compilation 506can involve or relate to the generation of a quantum program 508,generation or assembling of instructions 510 associated the quantumprogram 508, the determination and/or selection of quantum circuitry andquantum devices 512 for use in processing the job request, and/or inputdata 514 associated with the job request. Information (e.g., formattedinformation and instructions) from the adaptive compilation 506 can beforwarded to the quantum computer component 502 for processing by thequantum computer component 502.

The quantum computer component 502 can comprise a set of quantum chips,such as quantum chip 516, quantum chip 518, and quantum chip 520,wherein each of the quantum chips (e.g., 516, 518, 520, . . . ) cancomprise respective quantum devices and respective quantum circuitrythat can be used to perform various quantum operations on data, inresponse to execution of the quantum program 508 (e.g., execution of theinstructions of the quantum program 508) by the quantum computercomponent 502. The quantum computer component 502 also can comprise aset of simulator components 522, wherein a simulator component cansimulate or emulate the execution or operation of quantum circuitry andquantum devices. In some embodiments or implementations, one or moresimulator components of the set of simulator components 522 can beutilized to facilitate simulating or emulating the performance ofcertain tasks or operations by quantum circuitry and quantum devices.Such simulation can be performed, for example, when it is not feasibleto perform such certain tasks or operations using actual quantumcircuitry and quantum devices (e.g., using the set of quantum chips(e.g., 516, 518, 520)).

In response to executing the quantum program 508 and processing theinput data 514, the quantum computer component 502 can produce QOD 524(e.g., quantum data results) as an output. Result post-processing 526can be performed on the QOD 524 to generate post-process data results.As part of the result post-processing 526, analog-to-digital conversion(ADC) 528 can be performed to convert the analog QOD 524 to digital QOD,data compression 530 can be performed to compress the digital QOD,wherein post-processing and compression management 532 (e.g., by theCMC) can control the post-processing of the QOD 524, including thecompression of the digital QOD. The result post-processing 526 also caninclude quantum logic processing 534 to applying the quantum logic(e.g., quantum algorithm logic) to the compressed QOD to generatepost-processed data results 536. The post-processed data results can bestored in data storage 538 and/or can be provided to a desiredrecipient, such as a user, a service, or a requesting device.

The systems and/or devices have been (or will be) described herein withrespect to interaction between several components. It should beappreciated that such systems and components can include thosecomponents or sub-components specified therein, some of the specifiedcomponents or sub-components, and/or additional components.Sub-components could also be implemented as components communicativelycoupled to other components rather than included within parentcomponents. Further yet, one or more components and/or sub-componentsmay be combined into a single component providing aggregatefunctionality. The components may also interact with one or more othercomponents not specifically described herein for the sake of brevity,but known by those of skill in the art.

FIG. 6 illustrates a flow diagram of an example, non-limiting method 600that can control post-processing, including compression, of QOD that canbe output as data results from a quantum computer, in accordance withvarious aspects and embodiments of the disclosed subject matter. In someembodiments, the method 600 can be performed by, for example, a CMC, acompressor component, and/or a processor component, which can beassociated with a data store. Repetitive description of like elementsemployed in other embodiments described herein is or may be omitted forsake of brevity.

At 602, in response to receiving QOD, first compressed QOD can begenerated based at least in part on compression of the QOD at a firstcompression level, wherein the first compressed QOD can be provided tothe quantum logic component. The compressor component can receive theQOD (e.g., as converted from analog to digital form) from the quantumcomputer, which can produce the QOD (e.g., quantum output information)as data results based at least in part on input data that is input tothe quantum computer, a quantum program and associated instructions thatcan be executed on the quantum computer, comprising a collection ofquantum circuits and quantum devices, to perform operations on the inputdata and/or other data (e.g., other relevant data). The CMC can controlcompression of the QOD to have the compressor component (e.g., employinga first compressor sub-component) compress the QOD at the firstcompression level. Based at least in part on the compression of the QODat the first compression level, the compressor component can generatethe first compressed QOD, which can have a first data resolution. Thecompressor component can provide the first compressed QOD to the quantumlogic component for further processing.

At 604, a determination can be made regarding whether the firstcompressed QOD includes an amount of data that satisfies a definedthreshold amount of data to enable the first compressed QOD to beprocessed by the quantum logic component, based at least in part on adefined quantum logic processing criterion, to determine whether thequantum logic component is to process second compressed QOD that can bea less compressed version of the QOD than the first compressed QOD. Inaddition to the compressor component (e.g., employing the firstcompressor sub-component) compressing the QOD at the first compressionlevel, the compressor component (e.g., employing a second compressorsub-component) can compress the QOD at a second compression level togenerate second compressed QOD having a second data resolution, whichcan be higher than the first data resolution. The CMC can determinewhether the first compressed QOD (e.g., first compressed quantum outputinformation) includes an amount of data (e.g., sufficient data) (or hasa data resolution level) that satisfies (e.g., meets or exceeds) adefined threshold amount of data (or a defined threshold data resolutionlevel) to enable the first compressed QOD to be desirably processed(e.g., suitably or properly processed) by the quantum logic component(e.g., quantum algorithm logic of the quantum logic component), based atleast in part on the defined quantum logic processing criterion, whichcan indicate whether a stream of compressed data includes sufficientdata to enable it to be suitably or properly processed by the quantumlogic component. Based at least in part on the result of determiningwhether the first compressed QOD includes the amount of data (or has thedata resolution level) that satisfies the defined threshold amount ofdata (or has a data threshold level that satisfies the defined thresholddata resolution level) to be desirably processed by the quantum logiccomponent, the CMC can determine whether the quantum logic component isto process the second compressed QOD, wherein the second compressed QODcan be a less compressed version of the QOD than the first compressedQOD.

For instance, if the CMC determines that the first compressed QODincludes an amount of data that satisfies the defined threshold amountof data to be desirably processed by the quantum logic component, theCMC can determine that the quantum logic component can continue toprocess the first compressed QOD, can determine that the quantum logiccomponent does not have to be provided the second compressed QOD, andcan discard or facilitate discarding the second compressed QOD (and thenon-compressed QOD, except for any portion of the QOD that still remainsto be compressed at the first compression level). Conversely, if the CMCdetermines that the first compressed QOD does not include an amount ofdata sufficient to satisfy the defined threshold amount of data andenable it to be desirably processed by the quantum logic component, theCMC can determine that the quantum logic component is to be provided andis to process the second compressed QOD, can determine that the quantumlogic component can discontinue processing the first compressed QOD, andcan discard or facilitate discarding the first compressed QOD, or atleast any remaining portion thereof.

FIG. 7 depicts a flow diagram of another example, non-limiting method700 that control post-processing, including compression, of QOD outputas data results from a quantum computer, in accordance with variousaspects and embodiments of the disclosed subject matter. The method 700can be performed by, for example, a CMC, a compressor component, and/ora processor component, which can be associated with a data store.Repetitive description of like elements employed in other embodimentsdescribed herein is or may be omitted for sake of brevity.

At 702, QOD can be received from a quantum computer. The compressorcomponent and/or CMC can receive the QOD from the quantum computer,which can comprise a collection of quantum circuits and quantum devices.A quantum program can execute instructions to utilize desired quantumcircuits and quantum devices of the quantum computer to performoperations (e.g., quantum computing operations) on input data and/orother data (e.g., other relevant data). Based at least in part on theperformance of such operations on the input data and/or other data, thequantum computer or quantum program can determine and generate, as anoutput, the QOD.

At 704, first compressed QOD can be generated based at least in part oncompression of the QOD at a first compression level, wherein the firstcompressed QOD can be provided to quantum logic component. The QOD canbe converted from an analog form (e.g., analog signal) to a digital form(e.g., digital signal) by an ADC component. The compressor component canreceive the QOD (e.g., in digital form). The CMC can control compressionof the QOD to have the compressor component (e.g., employing a firstcompressor sub-component) compress the QOD at the first compressionlevel. Based at least in part on the compression of the QOD at the firstcompression level, the compressor component can generate the firstcompressed QOD, which can have a first data resolution. The compressorcomponent can provide the first compressed QOD to the quantum logiccomponent for further processing by the quantum logic component.

At 706, second compressed QOD can be generated based at least in part oncompression of the QOD at a second compression level, wherein the secondcompressed QOD can be a less compressed version of the QOD than thefirst compressed QOD. The CMC also can control compression of the QOD tohave the compressor component (e.g., employing a second compressorsub-component) compress the QOD at the second compression level. Basedat least in part on the compression of the QOD at the second compressionlevel, the compressor component can generate the second compressed QOD,which can have a second data resolution that can be higher than thefirst data resolution. In some embodiments, the compressor component canprovide the second compressed QOD to the quantum logic component inparallel with the first compressed QOD. Typically, while processing thefirst compressed QOD, if the quantum logic component also receives thesecond compressed QOD, the quantum logic component will not process thesecond compressed QOD, but will store the second compressed QOD until itis processed or discarded.

In certain embodiments, as more fully described herein, the CMC canemploy the machine learning component to adaptively determine, infer, orlearn a second compression level that can be used to compress the QOD toproduce (e.g., at least it is predicted to produce) second compressedQOD that can include sufficient data such that it can be desirablyprocessed (e.g., suitably or properly processed) by the quantum logiccomponent, in accordance with (e.g., to satisfy) a defined quantum logicprocessing criterion, which can indicate whether a stream of compresseddata includes sufficient data to enable it to be suitably or properlyprocessed by the quantum logic component. The machine learning componentcan perform a machine learning analysis on a portion (e.g., availableportion) of the first compressed QOD, previous data results (e.g., fromprevious job requests) and/or other information from the quantumcircuits, and/or feedback information relating to the first compressedQOD, which can be received from the quantum logic component. Based atleast in part on the results of the machine learning analysis, themachine learning component can adaptively determine, infer, or learnsuch a second compression level that can be used to facilitate producing(e.g., or is predicted to be able to facilitate producing) secondcompressed QOD that can include sufficient data such that it can bedesirably processed by the quantum logic component, in accordance withthe defined quantum logic processing criterion.

At 708, a determination can be made regarding whether the firstcompressed QOD includes sufficient data to be processed by the quantumlogic component, based at least in part on feedback information relatingto the first compressed QOD that is received from the quantum logiccomponent, and the defined quantum logic processing criterion. Thequantum logic component can perform validation checks on the dataresults from processing the first compressed QOD using the quantumlogic. The validation checks can indicate whether the first compressedQOD contains sufficient data (e.g., sufficient data points) to enablethe quantum logic component to desirably (e.g., suitably or properly)process the first compressed QOD, using the quantum logic, to produceusable data results. The CMC can receive, from the quantum logiccomponent, the feedback information, which can comprise informationrelating to the results of such validation checks. Based at least inpart on the feedback information, the CMC can determine whether thefirst compressed QOD includes sufficient data to be desirably processedby the quantum logic component, in accordance with (e.g., to satisfy)the defined quantum logic processing criterion.

If it is determined that the first compressed QOD includes sufficientdata, at 710, it can be determined that the first compressed QOD cancontinue to be processed by the quantum logic component. In response tothe CMC determining that the first compressed QOD includes sufficientdata to be desirably processed by the quantum logic component, the CMCcan determine that the quantum logic component can continue to processthe first compressed QOD. The CMC also can determine that the quantumlogic component does not have to be provided the second compressed QOD(e.g., any longer), and the CMC can discard or facilitate discarding thesecond compressed QOD (and the non-compressed QOD, except for anyportion of the QOD that still remains to be compressed at the firstcompression level). The method 700 can end at this point (if it isdetermined that the first compressed QOD can continue to be processed bythe quantum logic component).

Referring again to reference numeral 708, if, at 708, it is determinedthat the first compressed QOD does not include sufficient data (e.g., tobe desirably processed by the quantum logic component such that thedefined quantum logic processing criterion is satisfied), at 712, it canbe determined that the quantum logic component is to be provided and isto process the second compressed QOD, and is to discontinue processingthe first compressed QOD. For instance, in response to determining thatthe first compressed QOD does not include sufficient data to bedesirably processed by the quantum logic component, the CMC candetermine that the quantum logic component is to be provided and is toprocess the second compressed QOD. The CMC also can determine that thequantum logic component can discontinue processing the first compressedQOD, and can discard or facilitate discarding the first compressed QOD,or at least any remaining portion thereof.

At 714, a determination can be made regarding whether the secondcompressed QOD includes sufficient data to be processed by the quantumlogic component, based at least in part on feedback information relatingto the second compressed QOD that is received from the quantum logiccomponent, and the defined quantum logic processing criterion. Inconnection with using the quantum logic to further process the secondcompressed QOD, the quantum logic component can perform validationchecks on the data results from such processing of the second compressedQOD. The validation checks can indicate whether the second compressedQOD contains sufficient data to enable the quantum logic component todesirably (e.g., suitably or properly) process the second compressedQOD, using the quantum logic, to produce usable data results. The CMCcan receive, from the quantum logic component, the feedback information,which can comprise information relating to the results of suchvalidation checks on the second compressed QOD. Based at least in parton such feedback information, the CMC can determine whether the secondcompressed QOD includes sufficient data to be desirably processed by thequantum logic component, in accordance with (e.g., to satisfy) thedefined quantum logic processing criterion.

If it is determined that the second compressed QOD includes sufficientdata, at 716, it can be determined that the second compressed QOD cancontinue to be processed by the quantum logic component. In response tothe CMC determining that the second compressed QOD includes sufficientdata to be desirably processed by the quantum logic component, the CMCcan determine that the quantum logic component can continue to processthe second compressed QOD. The CMC also can determine that the quantumlogic component does not have to be provided the QOD (e.g., any longer),and the CMC can discard or facilitate discarding the QOD (e.g., thenon-compressed QOD, except for any portion of the QOD that still remainsto be compressed at the second compression level). The method 1200 canend at this point (if it is determined that the second compressed QODcan continue to be processed by the quantum logic component).

Referring again to reference numeral 714, if, at 714, it is determinedthat the second compressed QOD does not include sufficient data (e.g.,sufficient data to be desirably processed by the quantum logic componentsuch that the defined quantum logic processing criterion is satisfied),at 718, it can be determined that the quantum logic component is to beprovided and is to process the QOD, and is to discontinue processing thesecond compressed QOD. For instance, in response to determining that thesecond compressed QOD does not include sufficient data to be desirablyprocessed by the quantum logic component, the CMC can determine that thequantum logic component is to be provided and is to process the QOD(e.g., non-compressed QOD). The CMC also can determine that the quantumlogic component can discontinue processing the second compressed QOD,and can discard or facilitate discarding the second compressed QOD, orat least any remaining portion thereof.

FIG. 8 illustrates a flow diagram of an example, non-limiting method 800that can adaptively determine a compression level and compressionalgorithm to use for compressing QOD, in accordance with various aspectsand embodiments of the disclosed subject matter. The method 800 can beperformed by, for example, a CMC, a compressor component, a machinelearning component, and/or a processor component, which can beassociated with a data store. Repetitive description of like elementsemployed in other embodiments described herein is or may be omitted forsake of brevity.

At 802, first compressed QOD can be received from a first compressorsub-component of the compressor component. The first processorsub-component of the compressor component can receive QOD from thequantum computer component. Using a first compression algorithm, thefirst processor sub-component can compress the QOD at a firstcompression level to generate the first compressed QOD, which can have afirst data resolution. The machine learning component can receive thefirst compressed QOD, or a portion of such data stream, from the firstcompressor sub-component.

At 804, previous data relating to previous quantum operations performedby the quantum computer and/or quantum programs can be received, whereinthe previous data can comprise previous QOD associated with previousquantum programs that have been executed, information regarding previousgroups of quantum circuits and quantum devices that were used with theprevious quantum programs, and/or previous input data processed by theprevious quantum programs. The machine learning component can receivethe previous data relating to the previous quantum operations performedby the quantum computer and/or the quantum programs from a data store(e.g., a data store of the CMC, the quantum computer component, oranother component of the system).

At 806, feedback information relating to the first compressed QOD can bereceived from the quantum logic component. In some embodiments, inconnection with adaptively determining a compression level to use forcompressing the QOD to satisfy the applicable defined quantum logicprocessing criterion, the machine learning component can receive thefeedback information relating to the first compressed QOD from thequantum logic component.

At 808, the first compressed QOD, the previous data relating to theprevious quantum operations, and/or the feedback information relating tothe first compressed QOD can be analyzed. The machine learning componentcan analyze (e.g., can perform a machine learning, AI analysis, or otheranalysis on) the first compressed QOD, the previous data relating to theprevious quantum operations, and/or the feedback information.

At 810, based at least in part on the results of such analysis, a secondcompression level and second compression algorithm can be adaptivelydetermined, inferred, or learned, wherein compression of the QOD at thesecond compression level, using the second compression algorithm, canproduce second compressed QOD that can include, or can be predicted toinclude, sufficient data such that the second compressed QOD can bedesirably (e.g., suitably or properly) processed by the quantum logiccomponent, in accordance with the defined quantum logic processingcriterion. Based at least in part on the results of the analysis (e.g.,machine learning analysis, AI analysis, or other analysis), the machinelearning component can adaptively determine, infer, or learn a secondcompression level and second compression algorithm where compression ofthe QOD at the second compression level, using the second compressionalgorithm, can produce the second compressed QOD that can include, orcan be predicted to include, sufficient data such that the secondcompressed QOD can be desirably (e.g., suitably or properly) processedby the quantum logic component, in accordance with (e.g., to satisfy)the defined quantum logic processing criterion.

For simplicity of explanation, the methods and/or computer-implementedmethods are depicted and described as a series of acts. It is to beunderstood and appreciated that the disclosed subject matter is notlimited by the acts illustrated and/or by the order of acts, for exampleacts can occur in various orders and/or concurrently, and with otheracts not presented and described herein. Furthermore, not allillustrated acts can be required to implement the computer-implementedmethods in accordance with the disclosed subject matter. In addition,those skilled in the art will understand and appreciate that thecomputer-implemented methods could alternatively be represented as aseries of interrelated states via a state diagram or events.Additionally, it should be further appreciated that thecomputer-implemented methods disclosed hereinafter and throughout thisspecification are capable of being stored on an article of manufactureto facilitate transporting and transferring such computer-implementedmethods to computers. The term article of manufacture, as used herein,is intended to encompass a computer program accessible from anycomputer-readable device or storage media.

In order to provide a context for the various aspects of the disclosedsubject matter, FIG. 9 as well as the following discussion are intendedto provide a general description of a suitable environment in which thevarious aspects of the disclosed subject matter can be implemented. FIG.9 illustrates a block diagram of an example, non-limiting operatingenvironment in which one or more embodiments described herein can befacilitated. Repetitive description of like elements employed in otherembodiments described herein is or may be omitted for sake of brevity.With reference to FIG. 9, a suitable operating environment 900 forimplementing various aspects of this disclosure can also include acomputer 912. The computer 912 can also include a processing unit 914, asystem memory 916, and a system bus 918. The system bus 918 couplessystem components including, but not limited to, the system memory 916to the processing unit 914. The processing unit 914 can be any ofvarious available processors. Dual microprocessors and othermultiprocessor architectures also can be employed as the processing unit914. The system bus 918 can be any of several types of bus structure(s)including the memory bus or memory controller, a peripheral bus orexternal bus, and/or a local bus using any variety of available busarchitectures including, but not limited to, Industrial StandardArchitecture (ISA), Micro-Channel Architecture (MSA), Extended ISA(EISA), Intelligent Drive Electronics (IDE), VESA Local Bus (VLB),Peripheral Component Interconnect (PCI), Card Bus, Universal Serial Bus(USB), Advanced Graphics Port (AGP), Firewire (IEEE 1394), and SmallComputer Systems Interface (SCSI). The system memory 916 can alsoinclude volatile memory 920 and nonvolatile memory 922. The basicinput/output system (BIOS), containing the basic routines to transferinformation between elements within the computer 912, such as duringstart-up, is stored in nonvolatile memory 922. By way of illustration,and not limitation, nonvolatile memory 922 can include read only memory(ROM), programmable ROM (PROM), electrically programmable ROM (EPROM),electrically erasable programmable ROM (EEPROM), flash memory, ornonvolatile random access memory (RAM) (e.g., ferroelectric RAM(FeRAM)). Volatile memory 920 can also include random access memory(RAM), which acts as external cache memory. By way of illustration andnot limitation, RAM is available in many forms such as static RAM(SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rateSDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM),direct Rambus RAM (DRRAM), direct Rambus dynamic RAM (DRDRAM), andRambus dynamic RAM.

Computer 912 also can include removable/non-removable,volatile/non-volatile computer storage media. FIG. 9 illustrates, forexample, a disk storage 924. Disk storage 924 can also include, but isnot limited to, devices like a magnetic disk drive, floppy disk drive,tape drive, Jaz drive, Zip drive, LS-100 drive, flash memory card, ormemory stick. The disk storage 924 also can include storage mediaseparately or in combination with other storage media including, but notlimited to, an optical disk drive such as a compact disk ROM device(CD-ROM), CD recordable drive (CD-R Drive), CD rewritable drive (CD-RWDrive) or a digital versatile disk ROM drive (DVD-ROM). To facilitateconnection of the disk storage 924 to the system bus 918, a removable ornon-removable interface is typically used, such as interface 926. FIG. 9also depicts software that acts as an intermediary between users and thebasic computer resources described in the suitable operating environment900. Such software can also include, for example, an operating system928. Operating system 928, which can be stored on disk storage 924, actsto control and allocate resources of the computer 912. Systemapplications 930 take advantage of the management of resources byoperating system 928 through program modules 932 and program data 934,e.g., stored either in system memory 916 or on disk storage 924. It isto be appreciated that this disclosure can be implemented with variousoperating systems or combinations of operating systems. A user enterscommands or information into the computer 912 through input device(s)936. Input devices 936 include, but are not limited to, a pointingdevice such as a mouse, trackball, stylus, touch pad, keyboard,microphone, joystick, game pad, satellite dish, scanner, TV tuner card,digital camera, digital video camera, web camera, and the like. Theseand other input devices connect to the processing unit 914 through thesystem bus 918 via interface port(s) 938. Interface port(s) 938 include,for example, a serial port, a parallel port, a game port, and auniversal serial bus (USB). Output device(s) 940 use some of the sametype of ports as input device(s) 936. Thus, for example, a USB port canbe used to provide input to computer 912, and to output information fromcomputer 912 to an output device 940. Output adapter 942 is provided toillustrate that there are some output devices 940 like monitors,speakers, and printers, among other output devices 940, which requirespecial adapters. The output adapters 942 include, by way ofillustration and not limitation, video and sound cards that provide amethod of connection between the output device 940 and the system bus918. It should be noted that other devices and/or systems of devicesprovide both input and output capabilities such as remote computer(s)944.

Computer 912 can operate in a networked environment using logicalconnections to one or more remote computers, such as remote computer(s)944. The remote computer(s) 944 can be a computer, a server, a router, anetwork PC, a workstation, a microprocessor based appliance, a peerdevice or other common network node and the like, and typically can alsoinclude many or all of the elements described relative to computer 912.For purposes of brevity, only a memory storage device 946 is illustratedwith remote computer(s) 944. Remote computer(s) 944 is logicallyconnected to computer 912 through a network interface 948 and thenphysically connected via communication connection 950. Network interface948 encompasses wire and/or wireless communication networks such aslocal-area networks (LAN), wide-area networks (WAN), cellular networks,etc. LAN technologies include Fiber Distributed Data Interface (FDDI),Copper Distributed Data Interface (CDDI), Ethernet, Token Ring and thelike. WAN technologies include, but are not limited to, point-to-pointlinks, circuit switching networks like Integrated Services DigitalNetworks (ISDN) and variations thereon, packet switching networks, andDigital Subscriber Lines (DSL). Communication connection(s) 950 refersto the hardware/software employed to connect the network interface 948to the system bus 918. While communication connection 950 is shown forillustrative clarity inside computer 912, it can also be external tocomputer 912. The hardware/software for connection to the networkinterface 948 can also include, for exemplary purposes only, internaland external technologies such as, modems including regular telephonegrade modems, cable modems and DSL modems, ISDN adapters, and Ethernetcards.

One or more embodiments can be a system, a method, an apparatus and/or acomputer program product at any possible technical detail level ofintegration. The computer program product can include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of theone or more embodiments. The computer readable storage medium can be atangible device that can retain and store instructions for use by aninstruction execution device. The computer readable storage medium canbe, for example, but is not limited to, an electronic storage device, amagnetic storage device, an optical storage device, an electromagneticstorage device, a semiconductor storage device, or any suitablecombination of the foregoing. A non-exhaustive list of more specificexamples of the computer readable storage medium can include thefollowing: a portable computer diskette, a hard disk, a random accessmemory (RAM), a read-only memory (ROM), an erasable programmableread-only memory (EPROM or Flash memory), a static random access memory(SRAM), a portable compact disc read-only memory (CD-ROM), a digitalversatile disk (DVD), a memory stick, a floppy disk, a mechanicallyencoded device such as punch-cards or raised structures in a groovehaving instructions recorded thereon, and any suitable combination ofthe foregoing. A computer readable storage medium, as used herein, isnot to be construed as being transitory signals per se, such as radiowaves or other freely propagating electromagnetic waves, electromagneticwaves propagating through a waveguide or other transmission media (e.g.,light pulses passing through a fiber-optic cable), or electrical signalstransmitted through a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network can comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device. Computer readable programinstructions for carrying out operations of the disclosed subject mattercan be assembler instructions, instruction-set-architecture (ISA)instructions, machine instructions, machine dependent instructions,microcode, firmware instructions, state-setting data, configuration datafor integrated circuitry, or either source code or object code writtenin any combination of one or more programming languages, including anobject oriented programming language such as Smalltalk, C++, or thelike, and procedural programming languages, such as the “C” programminglanguage or similar programming languages. The computer readable programinstructions can execute entirely on the user's computer, partly on theuser's computer, as a stand-alone software package, partly on the user'scomputer and partly on a remote computer or entirely on the remotecomputer or server. In the latter scenario, the remote computer can beconnected to the user's computer through any type of network, includinga local area network (LAN) or a wide area network (WAN), or theconnection can be made to an external computer (for example, through theInternet using an Internet Service Provider). In some embodiments,electronic circuitry including, for example, programmable logiccircuitry, field-programmable gate arrays (FPGA), or programmable logicarrays (PLA) can execute the computer readable program instructions byutilizing state information of the computer readable programinstructions to personalize the electronic circuitry, in order toperform aspects of the disclosed subject matter.

Aspects of disclosed subject matter are described herein with referenceto flowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of thesubject disclosure. It will be understood that each block of theflowchart illustrations and/or block diagrams, and combinations ofblocks in the flowchart illustrations and/or block diagrams, can beimplemented by computer readable program instructions. These computerreadable program instructions can be provided to a processor of ageneral purpose computer, special purpose computer, or otherprogrammable data processing apparatus to produce a machine, such thatthe instructions, which execute via the processor of the computer orother programmable data processing apparatus, create method forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionscan also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks. The computer readable program instructions can also be loadedonto a computer, other programmable data processing apparatus, or otherdevice to cause a series of operational acts to be performed on thecomputer, other programmable apparatus or other device to produce acomputer implemented process, such that the instructions which executeon the computer, other programmable apparatus, or other device implementthe functions/acts specified in the flowchart and/or block diagram blockor blocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the disclosed subject matter. In this regard, each blockin the flowchart or block diagrams can represent a module, segment, orportion of instructions, which comprises one or more executableinstructions for implementing the specified logical function(s). In somealternative implementations, the functions noted in the blocks can occurout of the order noted in the Figures. For example, two blocks shown insuccession can be executed substantially concurrently, or the blocks cansometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

While the subject matter has been described above in the general contextof computer-executable instructions of a computer program product thatruns on a computer and/or computers, those skilled in the art willrecognize that this disclosure also can be implemented in combinationwith other program modules. Generally, program modules include routines,programs, components, data structures, etc. that perform particulartasks and/or implement particular abstract data types. Moreover, thoseskilled in the art will appreciate that the computer-implemented methodsdisclosed herein can be practiced with other computer systemconfigurations, including single-processor or multiprocessor computersystems, mini-computing devices, mainframe computers, as well ascomputers, hand-held computing devices (e.g., PDA, phone),microprocessor-based or programmable consumer or industrial electronics,and the like. The illustrated aspects can also be practiced indistributed computing environments where tasks are performed by remoteprocessing devices that are linked through a communications network.However, some, if not all aspects of this disclosure can be practiced onstand-alone computers. In a distributed computing environment, programmodules can be located in local and remote memory storage devices.

As used in this application, the terms “component,” “system,”“platform,” “interface,” and the like, can refer to and/or can include acomputer-related entity or an entity related to an operational machinewith one or more specific functionalities. The entities disclosed hereincan be either hardware, a combination of hardware and software,software, or software in execution. For example, a component can be, butis not limited to being, a process running on a processor, a processor,an object, an executable, a thread of execution, a program, and/or acomputer. By way of illustration, both an application running on aserver and the server can be a component. One or more components canreside within a process and/or thread of execution and a component canbe localized on one computer and/or distributed between two or morecomputers. In another example, respective components can execute fromvarious computer readable media having various data structures storedthereon. The components can communicate via local and/or remoteprocesses such as in accordance with a signal having one or more datapackets (e.g., data from one component interacting with anothercomponent in a local system, distributed system, and/or across a networksuch as the Internet with other systems via the signal). As anotherexample, a component can be an apparatus with specific functionalityprovided by mechanical parts operated by electric or electroniccircuitry, which is operated by a software or firmware applicationexecuted by a processor. In such a case, the processor can be internalor external to the apparatus and can execute at least a part of thesoftware or firmware application. As yet another example, a componentcan be an apparatus that provides specific functionality throughelectronic components without mechanical parts, wherein the electroniccomponents can include a processor or other method to execute softwareor firmware that confers at least in part the functionality of theelectronic components. In an aspect, a component can emulate anelectronic component via a virtual machine, e.g., within a cloudcomputing system.

In addition, the term “or” is intended to mean an inclusive “or” ratherthan an exclusive “or.” That is, unless specified otherwise, or clearfrom context, “X employs A or B” is intended to mean any of the naturalinclusive permutations. That is, if X employs A; X employs B; or Xemploys both A and B, then “X employs A or B” is satisfied under any ofthe foregoing instances. Moreover, articles “a” and “an” as used in thesubject specification and annexed drawings should generally be construedto mean “one or more” unless specified otherwise or clear from contextto be directed to a singular form. As used herein, the terms “example”and/or “exemplary” are utilized to mean serving as an example, instance,or illustration. For the avoidance of doubt, the subject matterdisclosed herein is not limited by such examples. In addition, anyaspect or design described herein as an “example” and/or “exemplary” isnot necessarily to be construed as preferred or advantageous over otheraspects or designs, nor is it meant to preclude equivalent exemplarystructures and techniques known to those of ordinary skill in the art.

As it is employed in the subject specification, the term “processor” canrefer to substantially any computing processing unit or devicecomprising, but not limited to, single-core processors;single-processors with software multithread execution capability;multi-core processors; multi-core processors with software multithreadexecution capability; multi-core processors with hardware multithreadtechnology; parallel platforms; and parallel platforms with distributedshared memory. Additionally, a processor can refer to an integratedcircuit, an application specific integrated circuit (ASIC), a digitalsignal processor (DSP), a field programmable gate array (FPGA), aprogrammable logic controller (PLC), a complex programmable logic device(CPLD), a discrete gate or transistor logic, discrete hardwarecomponents, or any combination thereof designed to perform the functionsdescribed herein. Further, processors can exploit nano-scalearchitectures such as, but not limited to, molecular and quantum-dotbased transistors, switches and gates, in order to optimize space usageor enhance performance of user equipment. A processor can also beimplemented as a combination of computing processing units. In thisdisclosure, terms such as “store,” “storage,” “data store,” datastorage,” “database,” and substantially any other information storagecomponent relevant to operation and functionality of a component areutilized to refer to “memory components,” entities embodied in a“memory,” or components comprising a memory. It is to be appreciatedthat memory and/or memory components described herein can be eithervolatile memory or nonvolatile memory, or can include both volatile andnonvolatile memory. By way of illustration, and not limitation,nonvolatile memory can include read only memory (ROM), programmable ROM(PROM), electrically programmable ROM (EPROM), electrically erasable ROM(EEPROM), flash memory, or nonvolatile random access memory (RAM) (e.g.,ferroelectric RAM (FeRAM)). Volatile memory can include RAM, which canact as external cache memory, for example. By way of illustration andnot limitation, RAM is available in many forms such as synchronous RAM(SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rateSDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM),direct Rambus RAM (DRRAM), direct Rambus dynamic RAM (DRDRAM), andRambus dynamic RAM (RDRAM). Additionally, the disclosed memorycomponents of systems or computer-implemented methods herein areintended to include, without being limited to including, these and anyother suitable types of memory.

What has been described above include mere examples of systems andcomputer-implemented methods. It is, of course, not possible to describeevery conceivable combination of components or computer-implementedmethods for purposes of describing this disclosure, but one of ordinaryskill in the art can recognize that many further combinations andpermutations of this disclosure are possible. Furthermore, to the extentthat the terms “includes,” “has,” “possesses,” and the like are used inthe detailed description, claims, appendices and drawings such terms areintended to be inclusive in a manner similar to the term “comprising” as“comprising” is interpreted when employed as a transitional word in aclaim. The descriptions of the various embodiments have been presentedfor purposes of illustration, but are not intended to be exhaustive orlimited to the embodiments disclosed. Many modifications and variationswill be apparent to those of ordinary skill in the art without departingfrom the scope and spirit of the described embodiments. The terminologyused herein was chosen to best explain the principles of theembodiments, the practical application or technical improvement overtechnologies found in the marketplace, or to enable others of ordinaryskill in the art to understand the embodiments disclosed herein.

What is claimed is:
 1. A system, comprising: a memory that storescomputer-executable components; and a processor, operatively coupled tothe memory, that executes computer-executable components, thecomputer-executable components comprising: a compressor component that,in response to receiving quantum output data, generates first compressedquantum output data based on compression of the quantum output data at afirst compression level, wherein the first compressed quantum outputdata is provided to quantum logic; and a compression managementcomponent that determines whether the first compressed quantum outputdata includes an amount of data that satisfies a defined thresholdamount of data to enable the first compressed quantum output data to beprocessed by the quantum logic, based on a defined quantum logicprocessing criterion, to determine whether the quantum logic is toprocess second compressed quantum output data that is a less compressedversion of the quantum output data than the first compressed quantumoutput data.
 2. The system of claim 1, wherein the compressor componentgenerates the second compressed quantum output data based on compressionof the quantum output data at a second compression level, wherein thesecond compressed quantum output data has a second data resolution levelthat is higher than a first data resolution level of the firstcompressed quantum output data.
 3. The system of claim 2, wherein, inresponse to determining that the first compressed quantum output dataincludes the amount of data that satisfies the defined threshold amountof data, based on the defined quantum logic processing criterion, thecompression management component determines that the second compressedquantum output data is to be discarded and data compression relating tothe second compression level is to be discontinued.
 4. The system ofclaim 2, wherein, in response to determining that the first compressedquantum output data does not include the amount of data sufficient tosatisfy the defined threshold amount of data, the compression managementcomponent determines that the second compressed quantum output data isto be processed by the quantum logic and facilitates providing thesecond compressed quantum output data to the quantum logic for quantumlogic processing.
 5. The system of claim 4, wherein the compressionmanagement component determines whether the second compressed quantumoutput data includes the amount of data that satisfies the definedthreshold amount of data to enable the second compressed quantum outputdata to be processed by the quantum logic, based on the defined quantumlogic processing criterion, to determine whether the quantum output datais to be processed by the quantum logic.
 6. The system of claim 5,wherein, in response to determining that the second compressed quantumoutput data does not include the amount of data sufficient to satisfythe defined threshold amount of data, the compression managementcomponent determines that the quantum output data is to be processed bythe quantum logic and facilitates providing the quantum output data tothe quantum logic for the quantum logic processing.
 7. The system ofclaim 1, wherein the compressor component comprises a first compressorsub-component and a second compressor sub-component, wherein the firstcompressor sub-component is linked with the second compressorsub-component, wherein the first compressor sub-component generates thefirst compressed quantum output data based on the compression of thequantum output data at the first compression level, wherein the secondcompressor sub-component generates the second compressed quantum outputdata based on compression of the quantum output data at a secondcompression level, and wherein the second compression level isdetermined based on the first compressed quantum output data.
 8. Thesystem of claim 7, wherein the computer-executable components furthercomprise a machine learning component that adaptively determines orinfers the second compression level and a compression algorithm to beused by the second compressor sub-component based on a result ofperforming a machine learning analysis on the first compressed quantumoutput data, previous data associated with previous quantum operationsor a previous quantum program, or information relating to quantumcircuits utilized by a quantum program to facilitate generation of thequantum output data or utilized by the previous quantum program tofacilitate generation of previous quantum output data.
 9. The system ofclaim 1, wherein the computer-executable components further comprise amachine learning component that infers or determines a compressionlevel, a corresponding data resolution level, and a correspondingcompression algorithm that will produce compressed quantum output datathat is sufficient to satisfy the defined threshold amount of data or adefined threshold data resolution level to enable the compressed quantumoutput data to be processed by the quantum logic, based on a result ofperforming a machine learning analysis on the quantum output data,previous data associated with previous quantum operations or a previousquantum program, or information relating to quantum circuits utilized bya quantum program to facilitate generation of the quantum output data orutilized by the previous quantum program to facilitate generation ofprevious quantum output data.
 10. The system of claim 1, wherein thecomputer-executable components further comprise a quantum programcomponent that, in response to execution of a quantum program, generatesthe quantum output data based on input data that is input to the quantumprogram, and wherein the quantum program component provides the quantumoutput data to the compressor component.
 11. The system of claim 10,wherein the quantum program processes the input data, utilizing a set ofquantum circuits, comprising quantum computing devices, and generatesthe quantum output data based on the processing of the input data.
 12. Acomputer-implemented method, comprising: in response to receivingquantum output information, generating, by a system operatively coupledto a processor, first compressed quantum output information based oncompressing the quantum output information at a first compression level,wherein the first compressed quantum output information is communicatedto quantum logic; and determining, by the system, whether the firstcompressed quantum output information has an amount of information thatsatisfies a defined threshold amount of information to enable the firstcompressed quantum output information to be processed by the quantumlogic, in accordance with a defined quantum logic processing criterion,to determine whether the quantum logic is to process second compressedquantum output information that is a less compressed version of thequantum output information than the first compressed quantum outputinformation.
 13. The computer-implemented method of claim 12, furthercomprising: in response to determining that the first compressed quantumoutput information has the amount of information that satisfies thedefined threshold amount of information, in accordance with the definedquantum logic processing criterion, determining, by the system, that thesecond compressed quantum output information is to be discarded andinformation compression relating to the quantum output information is tobe terminated.
 14. The computer-implemented method of claim 12, furthercomprising: in response to determining that the first compressed quantumoutput information does not have the amount of information to satisfythe defined threshold amount of information, determining, by the system,that the second compressed quantum output information is to be processedby the quantum logic; and communicating, by the system, the secondcompressed quantum output information to the quantum logic for quantumlogic processing.
 15. The computer-implemented method of claim 14,further comprising: generating, by the system, the second compressedquantum output information based on compressing the quantum outputinformation at a second compression level, wherein the second compressedquantum output information has a second information resolution that ishigher than a first information resolution of the first compressedquantum output information, and wherein the quantum output informationis generated based on processing input information using a quantumprogram; and determining, by the system, whether the second compressedquantum output information has the amount of information that satisfiesthe defined threshold amount of information, in accordance with thedefined quantum logic processing criterion, to determine whether thequantum output information or third compressed quantum outputinformation is to be processed by the quantum logic.
 16. Thecomputer-implemented method of claim 15, further comprising: in responseto determining that the second compressed quantum output informationdoes not have the amount of information to satisfy the defined thresholdamount of information, determining, by the system, that the quantumoutput information is to be processed by the quantum logic; andcommunicating, by the system, the quantum output information to thequantum logic for quantum logic processing.
 17. The computer-implementedmethod of claim 15, further comprising: generating, by the system, thethird compressed quantum output information based on compressing thequantum output information at a third compression level, wherein thethird compressed quantum output information has a third informationresolution that is higher than the second information resolution,wherein the third compressed quantum output information is a lesscompressed version of the quantum output information than the secondcompressed quantum output information.
 18. The computer-implementedmethod of claim 15, further comprising: in response to determining thatthe second compressed quantum output information does not have theamount of information to satisfy the defined threshold amount ofinformation, determining, by the system, that the third compressedquantum output information is to be processed by the quantum logic forthe quantum logic processing; and communicating, by the system, thethird compressed quantum output information to the quantum logic for thequantum logic processing.
 19. A computer program product thatfacilitates compressing quantum output data generated by a quantumcomputing circuit, the computer program product comprising a computerreadable storage medium having program instructions embodied therewith,the program instructions are executable by a processor to cause theprocessor to: in response to receiving the quantum output data, generatefirst compressed quantum output data, based on compression of thequantum output data at a first compression level, wherein the firstcompressed quantum output data is provided to quantum logic; anddetermine whether the first compressed quantum output data includes anamount of data points, associated with the quantum output data, thatsatisfies a defined threshold amount of data points to enable the firstcompressed quantum output data to be processed by the quantum logic, inaccordance with a defined quantum logic processing criterion, todetermine whether the quantum logic is to process second compressedquantum output data that is a less compressed version of the quantumoutput data than the first compressed quantum output data.
 20. Thecomputer program product of claim 19, wherein the quantum output data isgenerated based on processing input data using a quantum programassociated with the quantum computing circuit, and wherein the programinstructions are executable by the processor to cause the processor to:one of: in response to determining that the first compressed quantumoutput data includes the amount of the data points that satisfies thedefined threshold amount of data points, in accordance with the definedquantum logic processing criterion, determine that the second compressedquantum output data is to be discarded and data compression relating tothe quantum output data is to be discontinued; or in response todetermining that the first compressed quantum output data does notinclude the amount of the data points to satisfy the defined thresholdamount of data points, determine that the second compressed quantumoutput data is to be processed by the quantum logic, wherein the secondcompressed quantum output data has a second data resolution that ishigher than a first data resolution of the first compressed quantumoutput data, and transmit the second compressed quantum output data tothe quantum logic for quantum logic processing.